This application addresses the broad Challenge Area (01) Behavior, Behavioral Change, and Prevention and specific Challenge Area 01-HL-101: Develop innovative technologies and measurements to assess and provide real-time feedback on behavioral and environmental exposures for disease onset and progression for heart, lung, and blood disease. In October, 2008 the US Department of Health and Human Services issued the first-ever federally mandated Physical Activity Guidelines for Americans. The Guidelines reflect the view of the Physical Activity Guidelines Advisory Committee (PAGAC) and are based on an extensive review of the scientific literature on physical activity (PA) and health. In their report, the PAGAC points out the limited knowledge of the dose-response relationship between PA and health, and identifies poor measures of PA exposure as a major contributing factor to this gap in knowledge. Our application directly addresses this issue by applying innovative technologies to measure PA dose in a free- living environment. We will use these technologies to examine if habitual PA performed outside of purposeful exercise influences biomarkers of cardiovascular health. Although insufficient PA clearly correlates with an increased risk for cardiovascular disease (CVD), research evidence is equivocal regarding the effects of training on CVD risk factors (e.g. insulin action, triglycerides, blood pressure, and cholesterol). Research suggests increases in sedentary behavior may negate the benefits of training however this idea has not been explored experimentally. Our application will consider habitual free-living PA as a possible mechanism mediating the relationship between training and risk factors for cardiovascular disease. In order to elucidate the relationship between PA and biomarkers of cardiovascular disease risk, it is critical that valid, objective measures are used to quantify PA. We propose to use novel analytic techniques known as artificial neural networks (ANN) to process accelerometer-based measurements of PA. The first part of this project (Aim 1) will examine the ANN's sensitivity to change in PA dose by applying the ANN technique to distinguish three distinct patterns of habitual PA - Sedentary, Moderately Active, and Very Active. These three conditions represent common activity patterns that impact health. Accurately assessing changes to habitual PA levels that are relevant to public health will advance the field by further establishing a technique for application in population surveillance research and detection of changes in PA consequent to an intervention. The second part of this project (Aim 2) will apply the ANN methodology to examine the effect of free-living activity and inactivity levels, performed outside of training, on insulin action, blood pressure, triglycerides, cholesterol, and cardiorespiratory fitness following a 12-week exercise training trial in previously sedentary individuals with an elevated risk for CVD. Results from this study have the potential to impact how clinical exercise trials are conducted (e.g. require objective monitoring of PA outside of an exercise training trial) and how exercise is prescribed (e.g. reducing sedentary time AND maintaining sufficient PA). The Physical Activity Guidelines Advisory Committee advocates improved measures of physical activity exposure in order to elucidate the relationship between physical activity dose and health. To address this challenge we will apply and validate innovative accelerometer-based technologies for measuring physical activity to assess its sensitivity to detecting changes in dose of physical activity and to monitor activity outside of a training program designed to improve cardiorespiratory fitness and biomarkers of cardiovascular disease risk. Through improved measures of physical activity this project will promote a better understanding of how the dose of physical activity affects selected health outcomes.